I recently published matten, a small Rust library for working with multidimensional arrays. This is the first of four short posts introducing it. This one is about why it exists.
Rust is a great language for numerical and data-oriented work. But starting that work — just getting to the point where you have a matrix and can add two of them together — takes more effort than it probably should at the prototype stage.
The established libraries are capable and well-maintained. If you need performance, reach for ndarray or nalgebra. They are the right tools for production numerical code.
But they come with a learning curve: generic type parameters, storage abstractions, view types, lifetime considerations. That overhead is often worth it. It is not always worth it on day one of a proof of concept.
The gap matten fills is narrow and deliberate: making early-stage numerical Rust work feel less ceremonial, so you can spend the first hour on the problem rather than on the type system.
